adsabs/AstroCLIMB huggingface dataset:
Paper: The Star Formation Rate of the Milky Way as Seen by Herschel
Authors: D. Elia, S. Molinari, E. Schisano, J. D. Soler, M. Merello, D. Russeil, M. Veneziani, A. Zavagno, A. Noriega-Crespo, L. Olmi, M. Benedettini, P. Hennebelle, R. S. Klessen, S. Leurini, R. Paladini, S. Pezzuto, A. Traficante, D. J. Eden, P. G. Martin, M. Sormani, A. Coletta, T. Colman, R. Plume, Y. Maruccia, C. Mininni, S. J. Liu
Figure caption: Top: star formation rate (SFR) density profile estimated from the Hi-GAL observations in 0.5 kpc wide concentric rings around the Galactic center, shown in black filled circles. Fitting the relation in Equation (2) to the portion at R gal ≥ 5 kpc gives a = −0.28 ± 0.01 and b = −0.30 ± 0.16. The fit is plotted as a black dashed line. The green line shows the results of the visible-band observations considered in Guesten & Mezger (1982), rescaled by Kennicutt & Evans (2012) to the total SFR of 1.9 M ⊙ yr−1 reported in Chomiuk & Povich (2011). The blue line corresponds to the estimates obtained in Lee et al. (2016) by combining YSO near-IR photometry and cloud properties from millimeter-line observations. The red line shows the SFR profile of the galaxy NGC 6946, presented in Schruba et al. (2011) and adapted by Kennicutt & Evans (2012). The pink-shaded area is the region occupied by the models of Evans et al. (2022). Bottom: cumulative SFR profile as a function of the Galactocentric radius, also expressed as a percentage with respect to the total SFR (y-axis on the right-hand side). The vertical dotted lines indicate, from left to right, the Galactocentric radii corresponding to 50%, 90%, and 99% of the total SFR, respectively.
Paper: The Star Formation Rate of the Milky Way as Seen by Herschel
Authors: D. Elia, S. Molinari, E. Schisano, J. D. Soler, M. Merello, D. Russeil, M. Veneziani, A. Zavagno, A. Noriega-Crespo, L. Olmi, M. Benedettini, P. Hennebelle, R. S. Klessen, S. Leurini, R. Paladini, S. Pezzuto, A. Traficante, D. J. Eden, P. G. Martin, M. Sormani, A. Coletta, T. Colman, R. Plume, Y. Maruccia, C. Mininni, S. J. Liu
Figure caption: Map of the decimal logarithm of SFR density (divided by M ⊙ yr−1 kpc−2), across the Galactic plane. The spatial bins are of 0.5 × 0.5 kpc2, so that the absolute SFR inside each pixel can be obtained by exponentiating the displayed logarithm and then multiplying by a factor 4 kpc2. The Galactic center is at the [0, 0] position, while the gray “X” symbol indicates the position of the Sun. Gray dashed lines mark Galactic octants. Four spiral arms according to the prescription of Hou et al. (2009) are overplotted with four different tones of green; the correspondence between arms and colors is explained in the legend at the bottom-left corner.
Paper: The Star Formation Rate of the Milky Way as Seen by Herschel
Authors: D. Elia, S. Molinari, E. Schisano, J. D. Soler, M. Merello, D. Russeil, M. Veneziani, A. Zavagno, A. Noriega-Crespo, L. Olmi, M. Benedettini, P. Hennebelle, R. S. Klessen, S. Leurini, R. Paladini, S. Pezzuto, A. Traficante, D. J. Eden, P. G. Martin, M. Sormani, A. Coletta, T. Colman, R. Plume, Y. Maruccia, C. Mininni, S. J. Liu
Figure caption: Face-on view of the Milky Way representing the following quantities derived (with the same spatial binning used for Figure 5) from the Hi-GAL observations: (a) logarithm of number of pre-stellar Hi-GAL clumps per bin, ﹩{N}_{\mathrm{pre}};﹩ (b) logarithm of number of protostellar Hi-GAL clumps per bin, N pro; (c) star formation fraction, SFF; (d) median temperature (from modified blackbody fit) of protostellar clumps, ﹩\left\langle T\right\rangle ;﹩ (e) median logarithm of luminosity-to-mass ratio normalized to the solar values, ﹩\left\langle (L/M)/({L}_{\odot }/{M}_{\odot })\right\rangle ;﹩ (f) median bolometric temperature of protostellar clumps, ﹩\left\langle {T}_{\mathrm{bol}}\right\rangle ﹩. In each panel, the [0, 0] position corresponds to the Galactic center position, and the gray “X” symbol indicates the position of the Sun.
Paper: The Star Formation Rate of the Milky Way as Seen by Herschel
Authors: D. Elia, S. Molinari, E. Schisano, J. D. Soler, M. Merello, D. Russeil, M. Veneziani, A. Zavagno, A. Noriega-Crespo, L. Olmi, M. Benedettini, P. Hennebelle, R. S. Klessen, S. Leurini, R. Paladini, S. Pezzuto, A. Traficante, D. J. Eden, P. G. Martin, M. Sormani, A. Coletta, T. Colman, R. Plume, Y. Maruccia, C. Mininni, S. J. Liu
Figure caption: Star formation rate estimated from the Hi-GAL observations vs. the average molecular gas surface density (from Miville-Deschênes et al. 2017) in 1 kpc wide concentric rings around the Galactic center whose central radius is indicated by the colors. The bins corresponding to R gal ≤ 3 kpc and R gal > 3 kpc are marked with square and circle symbols, respectively. The dotted and the dashed lines indicate the linear fit to the SFR estimates at R gal ≥ 3 kpc (with slope n = 1.14 ± 0.07), and the KS relation (﹩{{\rm{\Sigma }}}_{\mathrm{SFR}}=2.5\times {10}^{-4}\,{{\rm{\Sigma }}}_{\mathrm{gas}}^{1.4}﹩), respectively.
Paper: The Star Formation Rate of the Milky Way as Seen by Herschel
Authors: D. Elia, S. Molinari, E. Schisano, J. D. Soler, M. Merello, D. Russeil, M. Veneziani, A. Zavagno, A. Noriega-Crespo, L. Olmi, M. Benedettini, P. Hennebelle, R. S. Klessen, S. Leurini, R. Paladini, S. Pezzuto, A. Traficante, D. J. Eden, P. G. Martin, M. Sormani, A. Coletta, T. Colman, R. Plume, Y. Maruccia, C. Mininni, S. J. Liu
Figure caption: Star formation rate, evaluated in bins of 0.5 kpc in the [x, y] plane, as a function of star formation fraction (i), and medians of temperature (ii), L/M ratio (iii), and bolometric temperature (iv) of protostellar clumps, respectively, all calculated in the same spatial bins. In this respect, they represent a pixel-to-pixel plot of Figure 5 vs. panels (c), (d), (e), and (f) of Figure 8, respectively. Gray symbols correspond to bins with ﹩{N}_{\mathrm{pro}}+{N}_{\mathrm{pre}}\lt 20﹩, considered statistically poor. In the leftmost panel, several of them give rise to vertical features, corresponding to recurring values like ﹩{N}_{\mathrm{pro}}{/(N}_{\mathrm{pro}}+{N}_{\mathrm{pre}})=\tfrac{1}{1},\tfrac{1}{2},\tfrac{1}{3},\tfrac{1}{4}﹩, etc.
Paper: The Star Formation Rate of the Milky Way as Seen by Herschel
Authors: D. Elia, S. Molinari, E. Schisano, J. D. Soler, M. Merello, D. Russeil, M. Veneziani, A. Zavagno, A. Noriega-Crespo, L. Olmi, M. Benedettini, P. Hennebelle, R. S. Klessen, S. Leurini, R. Paladini, S. Pezzuto, A. Traficante, D. J. Eden, P. G. Martin, M. Sormani, A. Coletta, T. Colman, R. Plume, Y. Maruccia, C. Mininni, S. J. Liu
Figure caption: Two examples (black and red histograms, respectively, in bins of 100 pc) of realizations of heliocentric distance distributions to be assigned, as a test, to Hi-GAL protostellar clumps devoid of a distance estimate, compared with the distance distribution for sources provided with a distance estimate (gray histogram; Elia et al. 2021).
Paper: The Star Formation Rate of the Milky Way as Seen by Herschel
Authors: D. Elia, S. Molinari, E. Schisano, J. D. Soler, M. Merello, D. Russeil, M. Veneziani, A. Zavagno, A. Noriega-Crespo, L. Olmi, M. Benedettini, P. Hennebelle, R. S. Klessen, S. Leurini, R. Paladini, S. Pezzuto, A. Traficante, D. J. Eden, P. G. Martin, M. Sormani, A. Coletta, T. Colman, R. Plume, Y. Maruccia, C. Mininni, S. J. Liu
Figure caption: Top: histograms of logarithm of SFR density for pixels of the map in Figure 5, classified as on-arm (black) and off-arm (gray), based on the fact that their minimum distance from at least one of the spiral arms displayed in Figure 5 is shorter or longer than 0.5 kpc, respectively. Middle: the same as in the top panel, but for pixels of the map of SFF in Figure 8, panel (c). Bottom: the same as in the previous panels, but for pixels of the map of ﹩\left\langle {L}_{\mathrm{bol}}/M\right\rangle ﹩ in Figure 8, panel (e).
Paper: The Star Formation Rate of the Milky Way as Seen by Herschel
Authors: D. Elia, S. Molinari, E. Schisano, J. D. Soler, M. Merello, D. Russeil, M. Veneziani, A. Zavagno, A. Noriega-Crespo, L. Olmi, M. Benedettini, P. Hennebelle, R. S. Klessen, S. Leurini, R. Paladini, S. Pezzuto, A. Traficante, D. J. Eden, P. G. Martin, M. Sormani, A. Coletta, T. Colman, R. Plume, Y. Maruccia, C. Mininni, S. J. Liu
Figure caption: Top: star formation rate (SFR) toward the Galactic plane in 3° × 0.2° bins in Galactic longitude and latitude, respectively. It should be noted that in the outer Galaxy the Hi-GAL latitude coverage follows the variations in the midplane position, or Galactic warp (Westerhout 1957). For a better rendering of the image dynamic range, the color scale follows a power law with exponent 0.4. The dotted lines indicate the location of the three most prominent SFR peaks. Bottom: SFR as a function of longitude, estimated from the sum of the results reported in the top panel across Galactic latitude.
Paper: The Star Formation Rate of the Milky Way as Seen by Herschel
Authors: D. Elia, S. Molinari, E. Schisano, J. D. Soler, M. Merello, D. Russeil, M. Veneziani, A. Zavagno, A. Noriega-Crespo, L. Olmi, M. Benedettini, P. Hennebelle, R. S. Klessen, S. Leurini, R. Paladini, S. Pezzuto, A. Traficante, D. J. Eden, P. G. Martin, M. Sormani, A. Coletta, T. Colman, R. Plume, Y. Maruccia, C. Mininni, S. J. Liu
Figure caption: Probable contribution to the overall SFR from sources lacking a distance estimate if they were all located at the same virtual distance. The dotted and dashed lines represent the median and the average of the real distance distribution, respectively.
Paper: Uncertainty and Bias of Cosmology and Astrophysical Population Model from Statistical Dark Sirens
Authors: Hang Yu, Brian Seymour, Yijun Wang, Yanbei Chen
Figure caption: Top: expected number of detections as a function of the redshift z at different values of h ≡ H 0/(100 km s−1 Mpc−1). From GW events, we can construct such a distribution as a function of D  L  first and then convert it to a function of z based on assumed cosmological parameters. Meanwhile, our astrophysical knowledge allows us to construct an expected distribution as a function of z from, e.g., galaxy catalogs. By comparing the two histograms, we can then constrain the value of the cosmological parameters. The bottom panel shows that the distribution is also affected by astrophysical models (e.g., the location of a peak in the BBH’s mass distribution μ  g ; see Section 3), which could mimic the effect of changing cosmological models. This indicates the significance of jointly analyzing astrophysical and cosmological parameters.
Paper: Uncertainty and Bias of Cosmology and Astrophysical Population Model from Statistical Dark Sirens
Authors: Hang Yu, Brian Seymour, Yijun Wang, Yanbei Chen
Figure caption: Similar to Figure 1, but now we plot the distribution as a function of the detector-frame mass of the primary black hole, ﹩{m}_{1}^{{\rm{d}}}﹩. Combining it with Figure 1 can thus be used to break the degeneracy between astrophysical and cosmological parameters.
Paper: Uncertainty and Bias of Cosmology and Astrophysical Population Model from Statistical Dark Sirens
Authors: Hang Yu, Brian Seymour, Yijun Wang, Yanbei Chen
Figure caption: Uncertainties on cosmological parameters (h, Ω m ) from the redshift histogram (cf. Figure 1), assuming we know the astrophysical model exactly. Throughout this work, we will use red crosses to denote the true values of the parameters (i.e., the values at which we evaluate the Fisher information matrix). The error ellipses indicate the 68% credible intervals. We predict an uncertainty on h of ±0.11, which agrees well with the gray dotted curve in Figure 9 in LIGO Scientific Collaboration et al. (2021d) obtained under the same assumptions.
Paper: Deep Narrowband Photometry of the M101 Group: Strong-line Abundances of 720 H II Regions
Authors: Ray Garner, J. Christopher Mihos, Paul Harding, Aaron E. Watkins, Stacy S. McGaugh
Figure caption: Top: ﹩\mathrm{log}({R}_{23})﹩ as a function of radius using each galaxy’s own R 25. Fitted lines are given to guide the eye to radial trends. Bottom: ﹩\mathrm{log}({{\rm{O}}}_{32})﹩ as a function of radius. In both plots, blue points are regions in M101 in our data, purple circles are regions in M101 from CHAOS, green plus signs are regions in NGC 5474, and orange stars are regions in NGC 5477. Black points with error bars show characteristic errors for both strong-line ratios as a function of radius and ratio.
Paper: Deep Narrowband Photometry of the M101 Group: Strong-line Abundances of 720 H II Regions
Authors: Ray Garner, J. Christopher Mihos, Paul Harding, Aaron E. Watkins, Stacy S. McGaugh
Figure caption: The KK04 oxygen abundances of M101 fitted with a simple exponential (dashed black line) and a broken exponential (solid black line). Regions in the turn-around region (orange circles), upper branch (blue triangles), and lower branch (green inverted triangles) are distinguished. Outside 1.3R 25, we display both the upper- and lower-branch solutions connected by a dotted line for each individual H II region. Characteristic error bars are ±0.02 dex for the upper branch, ±0.04 dex for the lower branch, and ±0.2 dex for the turn-around region. As indicated in the plot, a break in the abundance gradient was detected at 15.4 ± 0.5 kpc.
Paper: Deep Narrowband Photometry of the M101 Group: Strong-line Abundances of 720 H II Regions
Authors: Ray Garner, J. Christopher Mihos, Paul Harding, Aaron E. Watkins, Stacy S. McGaugh
Figure caption: From left to right, top to bottom: the Hα fluxes, Hβ fluxes, [O III]/Hβ ratio, R 23 ratio, [O III] fluxes, [O II] fluxes, [O II]/Hβ ratio, and O32 ratio for the 77 H II regions in M101 selected by the CHAOS group. The fluxes are measured in erg s−1 cm−2. All quantities shown are logarithmic. The points are colored by distance from the center of M101 in R 25. The dashed lines are 1:1 lines, and the values reported in the legend are the scatter from the 1:1 line, σ. The CHAOS spectroscopic flux is measured in 1″ slits, while our narrowband fluxes are measured in 3″ apertures, leading to the systematic offset seen in the line fluxes. The CHAOS Hα fluxes simulate our Hα flux measurements by adding the [N II] fluxes and subtracting the [S II] fluxes.
Paper: Deep Narrowband Photometry of the M101 Group: Strong-line Abundances of 720 H II Regions
Authors: Ray Garner, J. Christopher Mihos, Paul Harding, Aaron E. Watkins, Stacy S. McGaugh
Figure caption: The Hα, Hβ, [O III], and [O II] fluxes plotted against radius from the center of M101. H II regions in M101 are marked by circles, and H II regions in NGC 5474 are marked by plus signs; both are colored by local density of points in the plot. H II regions in NGC 5477 are marked by blue stars. The orange lines are the median values for M101 in bins of 0.1R 25, the standard deviation on each of the median values is ∼0.6, and the gray dashed lines mark the inner–outer disk of M101. In all plots, the corrections described in Section 3.2 have been applied.
Paper: Deep Narrowband Photometry of the M101 Group: Strong-line Abundances of 720 H II Regions
Authors: Ray Garner, J. Christopher Mihos, Paul Harding, Aaron E. Watkins, Stacy S. McGaugh
Figure caption:  A comparison of strong-line (blue lines) and T  e -based (orange lines) abundances for M101. Included are our simple and broken exponential fits for the KK04 abundance estimator, as well as the strong-line abundance gradient from Hu et al. (2018), who also used the KK04 abundance estimator. The T  e -based abundance gradients are from Kennicutt et al. (2003), Li et al. (2013) and Croxall et al. (2016). In all cases from the literature, their gradients have been converted to our choice of R 25 and our assumed distance.
Paper: Deep Narrowband Photometry of the M101 Group: Strong-line Abundances of 720 H II Regions
Authors: Ray Garner, J. Christopher Mihos, Paul Harding, Aaron E. Watkins, Stacy S. McGaugh
Figure caption:  The gradient of the outer regions of M101 in a quadrant rotated by 5°. Only those H II regions that satisfy 0.5 < R/R 25 < 1.8 were used in calculating gradients. The calibrations are as shown in the legend.
Paper: Deep Narrowband Photometry of the M101 Group: Strong-line Abundances of 720 H II Regions
Authors: Ray Garner, J. Christopher Mihos, Paul Harding, Aaron E. Watkins, Stacy S. McGaugh
Figure caption: Our measured R 23 data (black points) for M101 overlaid on the R 23 probability density contours for the simple exponential model (left) and broken exponential (right) generated using the best-fit Bayesian parameters described in the text. For both plots, the KK04 calibration was used to generate theoretical R 23 values.
Paper: Deep Narrowband Photometry of the M101 Group: Strong-line Abundances of 720 H II Regions
Authors: Ray Garner, J. Christopher Mihos, Paul Harding, Aaron E. Watkins, Stacy S. McGaugh
Figure caption: The KK04 metallicities and fitted radial gradients for the two satellites, NGC 5477 (top) and NGC 5474 (bottom). The solid purple and brown lines are the best-fit solutions, and the faded orange and green lines are 100 random walk fits that reflect the posterior distributions. Abundances are calculated via the upper branch of the R 23 relation (see text).
Paper: Deep Narrowband Photometry of the M101 Group: Strong-line Abundances of 720 H II Regions
Authors: Ray Garner, J. Christopher Mihos, Paul Harding, Aaron E. Watkins, Stacy S. McGaugh
Figure caption:  The spatial distribution of KK04 abundances for M101 (left), NGC 5477 (top right), and NGC 5474 (bottom right). Points are colored by KK04 abundance (color bar to the left), and angular and physical units are given.
Paper: Inferring Maps of the Sun’s Far-side Unsigned Magnetic Flux from Far-side Helioseismic Images Using Machine Learning Techniques
Authors: Ruizhu Chen, Junwei Zhao, Shea Hess Webber, Yang Liu, J. Todd Hoeksema, Marc L. DeRosa
Figure caption: (a) Magnetic-flux map converted from STEREO-A 304 Å image at 00:00 UT on 2014 March 13. (b) Same as panel (a) but for STEREO-B converted magnetic-flux map. (c) Far-side magnetic-flux map merged from both maps in panels (a) and (b). (d) Helioseismic far-side image taken at the same time as the map shown in panel (c). Both maps shown in panels (c) and (d) are in the same longitude–sin(latitude) coordinate system, where the longitude and latitude are the apparent disk coordinate. The heliographic coordinates are marked as dashed lines in both panels.
Paper: Inferring Maps of the Sun’s Far-side Unsigned Magnetic Flux from Far-side Helioseismic Images Using Machine Learning Techniques
Authors: Ruizhu Chen, Junwei Zhao, Shea Hess Webber, Yang Liu, J. Todd Hoeksema, Marc L. DeRosa
Figure caption: (a) An SDO/AIA 304 Å image of the Sun, taken at 00:00 UT on 2014 January 6. (b) AI-generated magnetic-flux map based on the 304 Å image shown in panel (a). (c) Simultaneous SDO/HMI-observed magnetic-flux map after a 3 × 3 boxcar smoothing for a comparison with panel (b).
Paper: Inferring Maps of the Sun’s Far-side Unsigned Magnetic Flux from Far-side Helioseismic Images Using Machine Learning Techniques
Authors: Ruizhu Chen, Junwei Zhao, Shea Hess Webber, Yang Liu, J. Todd Hoeksema, Marc L. DeRosa
Figure caption: Example showing the comparison of (a) STEREO-converted far-side magnetic-flux map and (b) helioseismic-image-converted far-side magnetic-flux map, both taken at 00:00 UT on 2014 March 13.
Paper: Inferring Maps of the Sun’s Far-side Unsigned Magnetic Flux from Far-side Helioseismic Images Using Machine Learning Techniques
Authors: Ruizhu Chen, Junwei Zhao, Shea Hess Webber, Yang Liu, J. Todd Hoeksema, Marc L. DeRosa
Figure caption: Comparison of EUV 304 Å total fluxes observed by the SDO/AIA and the two STEREO/EUVI instruments during the period of interest, after the STEREO/EUVI images are corrected for the instrumental degradation and recalibrated to match SDO/AIA values.
Paper: Inferring Maps of the Sun’s Far-side Unsigned Magnetic Flux from Far-side Helioseismic Images Using Machine Learning Techniques
Authors: Ruizhu Chen, Junwei Zhao, Shea Hess Webber, Yang Liu, J. Todd Hoeksema, Marc L. DeRosa
Figure caption: (a) Scatter plot comparing the values of magnetic-flux densities from the AI-generated maps and those from the SDO/HMI-observed maps. (b) Scatter plot comparing the globally averaged mean magnetic-flux densities from the AI-generated maps and those computed from the SDO/HMI-observed images. One point in the plot represents the results from one image in the test data set.
Paper: Inferring Maps of the Sun’s Far-side Unsigned Magnetic Flux from Far-side Helioseismic Images Using Machine Learning Techniques
Authors: Ruizhu Chen, Junwei Zhao, Shea Hess Webber, Yang Liu, J. Todd Hoeksema, Marc L. DeRosa
Figure caption: Unet deep neural network architecture for the model converting EUV 304 Å images into magnetic-flux maps.
Paper: Inferring Maps of the Sun’s Far-side Unsigned Magnetic Flux from Far-side Helioseismic Images Using Machine Learning Techniques
Authors: Ruizhu Chen, Junwei Zhao, Shea Hess Webber, Yang Liu, J. Todd Hoeksema, Marc L. DeRosa
Figure caption: Temporal evolution of the total magnetic flux for NOAA AR 11339 during its multiple disk passages on both near and far sides of the Sun.
Paper: Inferring Maps of the Sun’s Far-side Unsigned Magnetic Flux from Far-side Helioseismic Images Using Machine Learning Techniques
Authors: Ruizhu Chen, Junwei Zhao, Shea Hess Webber, Yang Liu, J. Todd Hoeksema, Marc L. DeRosa
Figure caption: Comparing the globally averaged mean magnetic-flux densities, computed from the SDO/HMI-observed magnetic-flux maps and the magnetic-flux maps converted from two sets of STEREO-observed 304 Å images.
Paper: Inferring Maps of the Sun’s Far-side Unsigned Magnetic Flux from Far-side Helioseismic Images Using Machine Learning Techniques
Authors: Ruizhu Chen, Junwei Zhao, Shea Hess Webber, Yang Liu, J. Todd Hoeksema, Marc L. DeRosa
Figure caption: Unet deep neural network architecture for the second machine-learning training, converting far-side helioseismic images into magnetic-flux maps.
Paper: Multiwavelength Observations of MWC 297: Constraints on Disk Inclination and Mass Outflow
Authors: William D. Vacca, Göran Sandell
Figure caption: Three-color image of MWC 297, generated from the PACS 70 (blue), 100 (green), and 160 (red) μm data on an asinh scale, of the region used to estimate total MIR fluxes. The arc detected in the SOFIA/FORCAST images, as well as the northeast core, offset by about 15″ from the center of MWC297, can be clearly seen. The arc is blue while the northeast core is considerably redder. A faint blue halo can also be seen centered on the northeast core. The dust ridge separating the central star in MWC297 from the northeast core can also be seen.
Paper: Multiwavelength Observations of MWC 297: Constraints on Disk Inclination and Mass Outflow
Authors: William D. Vacca, Göran Sandell
Figure caption: Spectrum of MWC 297 obtained with SpeX/IRTF. The Brackett and Paschen series of H have been marked along with the prominent O I lines. Pfund lines, as well as a weak CO (2–0) emission feature, can be seen at the longest wavelengths λ > 2.29 μm). Continuum jumps associated with all three H series are also clearly seen. The weak, broad, double-peaked feature at ∼2 μm is a residual telluric artifact. Aside from the P Cygni shape of the He I 1.083 μm, no convincing evidence of (stellar) absorption lines can be seen.
Paper: Multiwavelength Observations of MWC 297: Constraints on Disk Inclination and Mass Outflow
Authors: William D. Vacca, Göran Sandell
Figure caption: FORCAST images of MWC297 at 11, 19, 31, and 37 μm, displayed with asinh scaling (Lupton et al. 1999). North is up and east is left. The two Class II sources MWC 297 #1 and #2 can be clearly seen at 11.1 and 19.7 μm.
Paper: Multiwavelength Observations of MWC 297: Constraints on Disk Inclination and Mass Outflow
Authors: William D. Vacca, Göran Sandell
Figure caption: PACS 100 μm image (contours) overlaid on a logarithmically stretched FORCAST 31.5 μm image in color.
Paper: Multiwavelength Observations of MWC 297: Constraints on Disk Inclination and Mass Outflow
Authors: William D. Vacca, Göran Sandell
Figure caption: Three-color image generated by combining the FORCAST 11.1 (blue), 19.7 (green), and 31.5 (red) μm images.